Attribute sharing platform for data processing systems

ABSTRACT

A device may receive information for an attribute to include in a shared attribute library. The information may include an attribute identifier, data variables needed to compute a value of the attribute, and source code for computing the value of the attribute. The source code may be written in a first programming language. The device may receive a first request to compute the value of the attribute based on a first set of data variables from a first type of data application and a second request to compute the value of the attribute based on a second set of data variables from a second type of data application that is different than the first type of data application. The device may select a computing server, which may execute the first programming language, to compute the value of the attribute based on the first and second sets of data variables.

RELATED APPLICATION

This application is a continuation of U.S. patent application Ser. No.15/994,787, filed May 31, 2018 (now U.S. Pat. No. 10,120,926), which isincorporated herein by reference.

BACKGROUND

Organizations amass large volumes of data from a variety of differentsources, including from business transactions, social media, andinformation from sensor or machine-to-machine data. Organizations thenutilize various types of analytics to process the data using batchprocessing applications, stream processing applications, and/or anapplication programming interface (API) based processing applications toprocess and analyze the data for various reasons, including decisionmaking, forecasting, strategic marketing, and product development.

SUMMARY

According to some possible implementations, a method includes receiving,by a processor, information for an attribute to be included in a sharedattribute library. The information may include an attribute identifier,one or more data variables needed to compute a value of the attribute,and a source code for computing the value of the attribute. The sourcecode may be written in a first programming language. The method mayinclude receiving, by the processor, a first request to compute thevalue of the attribute based on a first set of data variables from afirst type of data processing application. The method may includereceiving, by the processor, a second request to compute the value ofthe attribute based on a second set of data variables from a second typeof data processing application that is different than the first type ofdata processing application. The method may include selecting, by theprocessor, a computing server from a plurality of computing servers. Thecomputing server may be configured to execute the first programminglanguage to compute the value of the attribute based on the first set ofdata variables and the second set of data variables. At least two of theplurality of computing servers may be associated with differentprogramming languages. The method may include receiving, by theprocessor, a first attribute value based on using the source code tocompute the value of the attribute based on the first set of datavariables, and receiving, by the processor, a second attribute valuebased on using the source code to compute the value of the attributebased on the second set of data variables. The method may includetransmitting, by the processor, the first attribute value as an inputfor the first type of data processing application, and transmitting, bythe processor, the second attribute value as an input for the secondtype of data processing application.

According to some possible implementations, a device may include amemory device configured to store a shared attribute library, and one ormore processors configured to receive information for an attribute to beincluded in the shared attribute library. The information may include anattribute identifier, one or more data variables needed to compute avalue of the attribute, and a source code for computing the value of theattribute. The source code may be written in a first programminglanguage. The one or more processors may receive a first request tocompute the value of the attribute based on a first set of datavariables from a first type of data processing application, and validatethe first request by verifying that the first set of data variablesincludes the one or more data variables needed to compute the value ofthe attribute. The one or more processors may receive a second requestto compute the value of the attribute based on a second set of datavariables from a second type of data processing application that isdifferent than the first type of data processing application, andvalidate the second request by verifying that the second set of datavariables includes the one or more data variables needed to compute thevalue of the attribute. The one or more processors may select acomputing server from a plurality of computing servers. The computingserver may be configured to execute the first programming language tocompute the value of the attribute based on the first set of datavariables and the second set of data variables. At least two of theplurality of computing servers may be associated with differentprogramming languages. The one or more processors may receive a firstattribute value based on using the source code to compute the value ofthe attribute based on the first set of data variables, and receive asecond attribute value based on using the source code to compute thevalue of the attribute based on the second set of data variables. Theone or more processors may transmit the first attribute value as aninput for the first type of data processing application, and transmitthe second attribute value as an input for the second type of dataprocessing application.

According to some possible implementations, a non-transitorycomputer-readable medium may store one or more instructions that, whenexecuted by one or more processors, cause the one or more processors toreceive information for an attribute to be included in a sharedattribute library. The information may include an attribute identifier,one or more data variables needed to compute a value of the attribute,and a source code for computing the value of the attribute. The sourcecode may be written in a first programming language. The one or moreinstructions, when executed by the one or more processors, may cause theone or more processors to receive a first request to compute the valueof the attribute based on a first set of data variables from a firsttype of data processing application, and receive a second request tocompute the value of the attribute based on a second set of datavariables from a second type of data processing application. The secondtype of data processing application may be different than the first typeof data processing application, and the first type of data processingapplication or the second type of data processing application may beimplementing a second programming language that is different than thefirst programming language. The one or more instructions, when executedby the one or more processors, may cause the one or more processors toselect a computing server from a plurality of computing servers. Thecomputing server may be configured to execute the first programminglanguage to compute the value of the attribute based on the first set ofdata variables and the second set of data variables. At least two of theplurality of computing servers may be associated with differentprogramming languages. The one or more instructions, when executed bythe one or more processors, may cause the one or more processors toreceive a first attribute value based on using the source code tocompute the value of the attribute based on the first set of datavariables, and receive a second attribute value based on using thesource code to compute the value of the attribute based on the secondset of data variables. The one or more instructions, when executed bythe one or more processors, may cause the one or more processors totransmit the first attribute value as an input for the first type ofdata processing application, and transmit the second attribute value asan input for the second type of data processing application.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A-1D are diagrams of an example implementation described herein.

FIG. 2 is a diagram of an example environment in which systems and/ormethods, described herein, may be implemented.

FIG. 3 is a diagram of example components of one or more devices of FIG.2.

FIG. 4 is a flow chart of an example process for sharing attributecomputation using an attribute sharing platform.

FIG. 5 is a flow chart of a further example process for sharingattribute computation using an attribute sharing platform.

FIG. 6 is a flow chart of a further example process for sharingattribute computation using an attribute sharing platform.

DETAILED DESCRIPTION

The following detailed description of example implementations refers tothe accompanying drawings. The same reference numbers in differentdrawings may identify the same or similar elements.

Data processing systems may employ multiple data processing applicationsto perform analytics on a large amount of data. Such data processingsystems may further employ different types of data processingapplications to process and/or analyze the data, or portions thereof(e.g., one or more sets of data), for use in forecasting and/or modelingaspects of a business. For example, the different types of dataprocessing applications employed in a data processing system may includea streaming application whereby a stream of data is received andprocessed, a batch application whereby a batch of data (i.e., tens ofrecords, hundreds of records, thousands of records, etc.) is receivedand processed, and/or an application programming interface (API) basedapplication whereby data is received and processed using API calls.

Each of the different types of data processing applications in the dataprocessing system may require the use of a same or common attribute whenprocessing data. A value of the attribute may be calculated or derivedbased on one or more data variables and used as input for the dataprocessing application in a machine learning system, an algorithm, amodel, or another type of computation. Example attributes include avalue that is calculated or computed as a sum of one or more datavariables, as an average of one or more data variables, as a standarddeviation of one or more data variables, as an equation based on onemore data variables, and/or the like. Oftentimes, the data processingapplications execute or implement different programming languages tocompute the value of the attribute. Thus, a source code for computingthe value of the attribute is more often duplicated or re-coded based onthe programming language that the data processing application isimplementing. Computing the value of the attribute differently and/orinconsistently make change management and maintenance in the dataprocessing system more tedious and/or more difficult.

Some implementations described herein provide an attribute sharingplatform including a shared attribute library. The attribute sharingplatform is configured to compute values of the attribute based ondifferent sets of data variables received from different types of dataprocessing applications. The values of the attribute are computed by theattribute sharing program according to predefined or standardized logicor source code that is stored in the shared attribute library. Theattribute sharing platform then sends the values of the attribute to thedifferent types of data processing applications as input for thedifferent types of data processing applications. Using standardizedlogic or source code to compute the values of the attributes ensuresthat the values of the attributes are being computed in a consistentmanner throughout the data processing system, including data processingsystems employing the different types of data processing applications.

The different types of data processing applications may, in someimplementations, differ in regard to how the data is processed (e.g.,via streaming, batch, API calls) and/or in terms of which programminglanguage is being implemented by the data processing applications. Insome implementations, the different types of data processingapplications may send the attribute sharing platform requests to computevalues of the attribute based on different sets of data variables (e.g.,sets of data variables specific to the data processing applicationmaking the request) contained in the requests and an attributeidentifier contained in the requests. The attribute sharing platform mayaccess the source code stored in the shared attribute library forcomputing the value of the attribute based on the attribute identifiercontained in the requests and based on the different sets of datavariables. In this way, the attribute sharing platform standardizes thecomputation of the values of the attribute, despite differences inregard to how the data is processed by the different types of dataprocessing applications and/or differences in the programming languagesbeing implemented by the data processing applications.

In some implementations, the attribute sharing platform further selectsa computing server to compute the values of the attribute. The computingserver can be selected from a plurality of computing servers based onmapping the programming language that the source code is written in andthe programming language that the computing server is executing. Thevalues of the attributes may be computed by the computing serverselected from the plurality of computing servers and sent to the dataprocessing applications for input. In this way, the attribute sharingplatform facilitates sharing of the source code for computing the valuesof the attribute in a language agnostic manner by virtue of mapping theprogramming language that the source code associated with the attributeidentifier is written in and the programming language that the computingserver is executing.

Moreover, the values of attributes that are computed based on the sharedsource code may be used as input for the different types of dataprocessing applications. The attribute sharing platform allows thevalues of the attributes to be computed in a same or similar manneracross multiple data processing applications of a data processingsystem, thereby obviating the need for recoding and/or deduplicating thesource code needed to compute the values in different programminglanguages and conserving processing resources needed to compute thevalues of the attributes. Sharing the sourced code for computing theattribute across different types of data processing applications in adata processing system also conserves an amount of memory and/or storageresources needed to store source code, software, and/or data variablesneeded to compute the values of the attribute in different programminglanguages. In this way, change management and/or maintenance in the dataprocessing system may be simplified. Additionally, the attribute sharingplatform may anticipate when the computation of values of the attributesmay be requested and may more easily scale computing resources on demandor as needed, thereby conserving processing resources, memory resources,and/or the like.

FIGS. 1A-1D are diagrams of an overview of an example implementation 100described herein. As shown in FIGS. 1A-1D, example implementation 100may include a shared attribute library builder, an attribute sharingplatform, a plurality of computing servers, a plurality of dataprocessing applications, and a plurality of clients. The attributesharing platform may include a shared attribute library.

As shown in FIG. 1A, and by reference number 102, the shared attributelibrary builder may send information for attributes to be included inthe shared attribute library. For example, the shared attribute librarybuilder may be used to create, populate, build, and/or updateinformation for the attributes to be included in the shared attributelibrary of the attribute sharing platform. In some implementations, theshared attribute library builder may be accessed by a user to sendinformation associated with the attributes for storage as records in theshared attribute library of the attribute sharing platform.

As shown by reference number 104, the attribute sharing platformreceives the information from the shared attribute library builder andstores the information for the attributes in the shared attributelibrary. The user may define or specify the attributes in the sharedattribute library of the attribute sharing platform based on informationsuch as an attribute identifier, one or more data variables needed tocompute values of the attribute (i.e., the inputs), a source code neededto compute the values of the attribute, a programming languageidentifier for a programming language that the source code is writtenin, and/or the like.

In some implementations, the shared attribute library builder mayinclude a user interface by which the user may input the information forinclusion in the shared attribute library. For example, the userinterface may cause a variety of information to be displayed to the userin a manner designed to enable the user to create a new record forstorage in the attribute sharing platform. In some implementations, theuser interface may enable the user to generate, edit, add, delete,activate, or deactivate one or more data objects used to identify theattribute using the attribute identifier, identify the one or morevariables needed to compute the values of the attribute, and/or identifythe programming language that the attribute is written in using theprogramming language identifier. In this way, the shared attributelibrary builder enables the user to generate the shared attributelibrary based on inputting of the data objects and linking the dataobjects to a pre-written source code used to compute the values of theattribute. In some implementations, the attribute identifier, datavariables, source code, and programming language identifier are storedin a single data structure (e.g., table) of the shared attributelibrary. Alternatively, or additionally, the attribute identifier, datavariables, source code, and programming language identifier are storedin multiple data structures forming the shared attribute library. Thedata in the data structures may be linked and/or mapped together basedon any of the attribute identifier, data variables, source code,programming language identifier, combinations thereof, and/or the like.In some implementations, the shared attribute library is a repositorycontaining various records associated with attributes to be sharedand/or consistently computed across data processing applications of adata processing system.

As further shown in FIG. 1A, and by reference number 106, the attributesharing platform may additionally store mapping information for use inselecting a computing server from a pool of computing servers to computethe values of the attributes. In some implementations, the mappinginformation may include a computing server identifier (e.g., a name oraddress of the computing server) and a programming language identifierthat identifies the programming language executed by the computingserver. The computing server identifier may be used to identify ordistinguish the computing server selected for computing the values ofthe attribute and the programming language identifier may be used toidentify the programming language being executed or implemented by thecomputing server. In this way, the attribute sharing platform can selectwhich computing server will be used to compute the value of theattribute based on the mapping between which programming language theattribute is written in and which programming language the computingserver executes to compute the value. As shown in FIG. 1A, the sharedattribute library and the mapping information may each includeprogramming language identifiers, which may be used to map the attributeidentifier to the computing server to ensure standardized, consistentcomputation of the values of the attributes. In some implementations, acomputing server executes a single programming language. In someimplementations, a computing server executes multiple programminglanguages which may be used to compute the values of the attribute. Insome implementations, a first computing server executes a singleprogramming language, and a second computing server executes multipleprogramming languages.

As shown in FIG. 1B, a pool of client devices, (i.e., Client 1, Client2, and Client N, where N>2) is provided, whereby each client device inthe pool of client devices is configured to execute, host, store, run,or otherwise access one or more of the data processing applications foranalyzing data. Such client devices may access different types of dataprocessing applications, for example, Client 1 may access a first dataprocessing application that may be a batch application, Client 2 mayaccess a second data processing application that may be a streamingapplication, and Client N may access a third data processing applicationthat may be an API-based application. Although three different types ofdata processing applications are shown in FIG. 1B, use of more or lessthan three different types of data processing applications in the dataprocessing system is contemplated.

In some implementations, the different types of data processingapplications are configured to access and/or communicate with theattribute sharing platform via a common interface and standardizedrequest to increase the efficiency at which the values of the attributesare computed. For example, the different types of data processingapplications may access and/or communicate with the attribute sharingplatform based on a request-response pair interface, such as RemoteProcedure Calls (RPCs), Google® Remote Procedure Calls (gRPCs), and/orthe like. The attribute sharing platform may likewise respond to therequests from the different types of data processing applications usingthe request-response pair interface. The different types of dataprocessing applications, using the request-response pair interface, mayinclude, in the requests, a common attribute sharing platform identifierto ensure routing of the requests to the attribute sharing platformbased on the attribute sharing platform identifier. The requests fromthe different types of data processing applications further include theattribute identifier and a set of data variables used to compute thevalues of the attribute. In this way, the requests received by theattribute sharing platform are standardized irrespective of the type ofdata processing application sending the request. This may conservecomputing resources on the attribute sharing platform relative to theplatform having to process non-standardized requests. In someimplementations, the attribute sharing platform may recognize whichattribute to compute based on the attribute identifier provided in therequest and the attribute will be computed based on the set of datavariables provided in the request.

Referring still to FIG. 1B, and by reference number 108, a first dataprocessing application (i.e., Data Processing Application 1) may send afirst request to the attribute sharing platform to compute a value ofthe attribute based on a first set of data variables (i.e., data set 1).The first request may include the attribute sharing platform identifier,a first attribute identifier (i.e., Attribute 1), and the first dataset. As shown by reference number 110, the attribute sharing platformmay receive the first request and access the shared attribute library togather information needed to compute the value of the attribute based onthe first data set. For example, the attribute sharing platform mayaccess the shared attribute library based on the attribute identifiercommunicated in the request.

In some implementations, the attribute sharing platform may validate thefirst request by verifying that the first set of data variables receivedfrom the first data processing application includes the one or more datavariables needed to compute the value of the first attribute. In thisway, the attribute sharing platform ensures consistency with respect tothe type of data being used to compute the value of the attributes. Forexample, multiple computation for the values of the attribute may bebased on a same quantity of data points and/or a same type of dataattributes.

As an example, the value of the first attribute may be computedaccording to an equation based on manipulating a first set of datavariables that includes three data variables. A first data variable maybe an amount specified in dollars, a second data variable may be aninterest rate specified as a percentage, and a third variable may be alength of time specified in months. In this case, if the data processingapplication does not send the first set of data variables in the correctorder, as specified according to the shared attribute library, and/ordoes not send the correct number of data variables needed to perform thecomputation, then the attribute sharing platform may deny the request.Similarly, if the data processing application does not send three datavariables in the correct format (e.g., in dollars, as the percentage,and/or months), and, for example, instead sends a string of alphabeticaltext, then the attribute sharing platform may deny the request. In thisway, the attribute sharing platform ensures consistency in computationof the values of the attribute. Additionally, the attribute sharingplatform can conserve computing resources that would otherwise be wastedattempting to compute values of attributes where the correct variablesare not received.

As further shown in FIG. 1B, and by reference number 112, the attributesharing platform may select the computing server configured to executethe programming language that matches the programming language of thefirst attribute in the shared attribute library, so that the computingserver can execute the source code and compute a first value of thefirst attribute (i.e., a first attribute value). For example, theattribute sharing platform may perform a lookup to determine that thesource code for the first attribute is written in a first programminglanguage. The attribute sharing platform may map the first attributeidentifier to the computing server based on the computing server beingconfigured to execute the first programming language. In this way, theattribute sharing platform shares the source code for computing thevalue of the attribute and ensures consistent, standardized computationof values of the attribute.

As further shown in FIG. 1B, and by reference number 114, the attributesharing platform may request computation of the value of the attributeby a second computing server (i.e., Computing Server 2). The secondcomputing server may compute the value of the input based on executingthe source code and including, as input in the source code, the firstset of data variables received in the request from the first dataprocessing application. As shown by reference number 116, the secondcomputing server may send the first value of the attribute uponcomputing the first value of the attribute. As shown by reference number118, the attribute sharing platform may respond to the request from thefirst data processing application and transmit the first value of theattribute. As shown by reference number 120, the first data processingapplication may receive the first value of the attribute and input thefirst value of the attribute for use in the batch application. In someimplementations, the first data processing application may use the firstvalue of the attribute as input in a machine learning system to train amodel, as input to an algorithm or equation used to analyze data, or asinput for any other type of computation.

Referring now to FIG. 1C, and by reference number 122, a second dataprocessing application may send a second request to the attributesharing platform to compute the value of the attribute based on a secondset of data variables (i.e., data set 2). That is, the second dataprocessing application may request computation of the same attributethat was requested by the first data processing application as describedabove with respect to FIG. 1B. The second data processing applicationmay be a different type of data processing application than the firstdata processing application. For example, the second data processingapplication may be a streaming application whereas the first dataprocessing applications may be a batch application.

In some implementations, the first data processing application is thebatch application which may operate based on a trigger. For example, thetrigger may be a time-based trigger whereby the first data processingapplication sends the first request to compute the value of theattribute according to a day, a time, an expiration of a time period,and/or the like. In some implementations, the trigger may be a call orrequest from an API endpoint associated with the API-based dataprocessing application. Other triggers are contemplated, for example,such as event triggers, throughput triggers, and/or the like. In someimplementations, the first data processing application and/or the seconddata processing application may be an application that does not operatebased on a trigger. In addition to being different types of dataprocessing applications, the first data processing application mayoptionally implement different programming languages. In this way, theattribute sharing platform ensures consistent, standardized calculationof the same attribute (e.g., Attribute 1) based on different data sets(i.e., data set 1 from FIG. 1B and data set 2 from FIG. 1C).

In some implementations, the first request for computation of the valueof the first attribute from the first data processing application andthe second request for computation of the value of first attribute fromthe second data processing application may include a same or similarformat. For example, the first request for computation of the value ofthe first attribute from the first data processing application and thesecond request for computation of the value of the first attribute fromthe second data processing application may be communicated using therequest-response pair interface, such as the RPC or gRPC interface.Further, the first request for computation of the value of the firstattribute from the first data processing application and the secondrequest for computation of the value of the first attribute from thesecond data processing application may include the attribute sharingplatform identifier, the attribute identifier, and the data variablesused to compute the value of the first attribute. The data variablessent in the requests for computation of the value of the first attributefrom the first data processing application and the second dataprocessing application may include a same quantity of data points, asame type of data attributes (e.g., numeric data, text data, etc.),and/or a same unit of measurement (e.g., dollar amounts, time,percentages, measurements, etc.), but possibly different values of thedata variables.

As further shown in FIG. 1C, and by reference number 124, the attributesharing platform may receive the second request for computation of thevalue of the first attribute. In some implementations, the attributesharing platform may optionally validate the second request by verifyingthat the second set of data variables received from the second dataprocessing application includes the one or more data variables needed tocompute the value of the first attribute. In this way, the attributesharing platform ensures consistency with respect to the type of databeing used to compute the value of the first attribute. For example,computation for the values of the first attribute may be based on setsof data having the same quantity of data points, the same type of dataattributes, and/or the same unit of measurement for the data attributes.

As shown by reference number 126, the attribute sharing platform mayselect the second computing server to compute the value of the firstattribute. In this case, the selection may be based on mappinginformation stored by the attribute sharing platform. For example, theattribute sharing platform may select the second computing server tocompute the value of the first attribute based on the first attributeidentifier being mapped to source code written in the first programminglanguage and the second computing server being configured to execute thefirst programming language. As shown by reference number 128, theattribute sharing platform may send a request to the second computingserver for computation of a second value of the attribute (i.e., asecond attribute value) based on the second set of data variables. Asshown by reference number 130, the computing server may send the secondvalue of the attribute to the second data processing application uponcomputing the second value of the attribute. As shown by referencenumber 132, the attribute sharing platform may respond to the requestfrom the second data processing application and transmit the secondvalue of the attribute. As shown by reference number 134, the seconddata processing application may receive the second value of theattribute and input the second value of the attribute for use in thestreaming application. The second data processing application may usethe second value of the attribute as input in a model to makepredictions or forecasts on data, as input in an algorithm to analyzedata, as input in a machine training or a machine learning application,and/or the like.

Referring now to FIG. 1D, in some implementations, the attribute sharingplatform may further process a request for an Nth attribute (i.e.,Attribute N) that is different from the first attribute. In this case,the attribute sharing platform may map the Nth attribute to an Nthcomputing server (i.e., Computing Server N) that is different than thecomputing server used to compute the first attribute, based on how theNth attribute is defined in the shared attribute library of theattribute sharing platform. For example, the attribute sharing platformmay select the Nth computing server, from the pool of computing servers,for computing the value of the Nth attribute based on the Nth attributeidentifier being mapped to source code written in an Nth programminglanguage and the Nth computing server being configured to execute theNth programming language.

As further shown in FIG. 1D, and by reference number 136, an Nth dataprocessing application may send the request to compute the value of theNth attribute based on an Nth set of data variables. In someimplementations, the Nth data processing application may be a differenttype of data processing application than the first data processingapplication and/or the second data processing application. For example,the Nth data processing application may include an API-based applicationwhereas the first data processing application is the batch applicationand the second data processing application is the streaming application.In some implementations, the Nth data processing application mayoptionally execute a different programming language than the first dataprocessing application and/or the second data processing application.For example, the Nth data processing application may execute the Nthprogramming language which may be different than the programminglanguage executed by one or more of the other data processingapplications.

In some implementations, the request from the Nth data processingapplication may include the same format as the request from the firstdata processing application and the second data processing application.For example, the request from the Nth data processing application may besent according to the request-response pair interface and include theattribute sharing platform identifier thereby ensuring routing of therequest to the attribute sharing platform based on the attribute sharingplatform identifier. In this way, the requests received by the attributesharing platform are standardized irrespective of the type of dataprocessing application sending the request.

As shown by reference number 138, the attribute sharing platform mayreceive the request from the Nth data processing application. Therequest from the Nth data processing application may include anattribute identifier that identifies the Nth attribute and datavariables used to compute the Nth attribute. Additionally, in someimplementations, the attribute sharing platform may validate the requestas described above. As shown by reference number 140, the attributesharing platform may select the Nth computing server from the pluralityof computing servers based on mapping the programming language used tocompute the Nth attribute and the programming language executed by theNth computing server. For example, the attribute sharing platform maydetermine, based on mapping information stored by the attribute sharingplatform, that the Nth computing server executes the programminglanguage needed to compute the Nth attribute based on the Nth attributebeing written in the same programming language.

As further shown in FIG. 1D, and by reference number 142, the attributesharing platform may request computation of the value of the Nthattribute. As shown by reference number 144, the computing server maysend the value of the Nth attribute after computing the value of the Nthattribute. As shown by reference number 146, the attribute sharingplatform may respond to the Nth data processing application bytransmitting the value of the attribute N (i.e., the Nth attributevalue). As shown by reference number 148, the Nth data processingapplication may input the value of the Nth attribute for use inprocessing data by the Nth data processing application. In this way, theattribute sharing platform enables the logic or source code forcomputing the same attributes to be shared among different dataprocessing applications in the data processing system, thereby ensuringconsistent computation of the same attributes in a language agnosticmanner.

As indicated above, FIGS. 1A-1D are provided merely as examples. Otherexamples are possible and may differ from what was described with regardto FIGS. 1A-1D.

FIG. 2 is a diagram of an example environment 200 in which systemsand/or methods, described herein, may be implemented. As shown in FIG.2, environment 200 may include one or more client devices 210, one ormore application servers 220, an attribute sharing platform 240,computing resource 250, and a network 260. Devices of environment 200may interconnect via wired connections, wireless connections, or acombination of wired and wireless connections.

Client device 210 includes one or more devices capable of sending,receiving, generating, storing, processing, and/or providing informationassociated with sharing attribute computations using an attributesharing platform. For example, client device 210 may include acommunication and/or computing device, such as a laptop computer, atablet computer, a handheld computer, a gaming device, a mobile phone(e.g., a smart phone, a radiotelephone, etc.), a wearable communicationdevice (e.g., a smart wristwatch, a pair of smart eyeglasses, etc.), ora similar type of device. Client device 210 may include one or moreinterfaces, applications, or services designed to enable client device210 to communicate with network 260 and application server 220 topresent a user interface on a display of client device 210, such as anapplication designed to communicate with a data processing platformand/or the like.

Application server 220 includes one or more devices capable of sending,receiving, storing, processing, and/or providing information associatedwith the sharing of the attribute computations using the attributesharing platform. For example, application server 220 may include aserver device, a data center device, or a similar device. Applicationserver 220 is configured, for example, to receive data from one or moredata sources (e.g., business sources, social media sources, sensor ormachine-to-machine data, etc.) to identify attributes needed forprocessing the received data, request the attributes from the attributesharing platform, receive values of the attributes, and input the valuesof the attributes for processing data. The application servers mayinclude servers implementing batch applications, streaming applications,API-based applications, and/or the like.

Cloud computing environment 230 includes an environment that deliverscomputing as a service, whereby shared resources, services, etc. may beprovided to attribute sharing platform 240. Cloud computing environment230 may provide computation, software, data access, storage, and/orother services that do not require end-user knowledge of a physicallocation and configuration of a system and/or a device that delivers theservices. As shown, cloud computing environment 230 may includeattribute sharing platform 240 and computing resource 250.

Attribute sharing platform 240 may include one or more devices capableof receiving and responding to requests to compute values of theattribute from client device 210, application server 220, the network260, or combinations thereof. Attribute sharing platform 240 mayvalidate requests received from client device 210, application server220, and/or the network by verifying that the set of data variablesreceived in the request includes the one or more data variables neededto compute the value of the attribute. Attribute sharing platform 240may determine, using the attribute identifier, which attribute tocompute and select a computing server from the plurality of computingservers as described herein. In some implementations, attribute sharingplatform 240 maps the attribute to the computing server based on thecomputing server being configured to execute the first programminglanguage and selecting the computing server based on the mapping.

In some implementations, the computing servers selected by the attributesharing platform to compute values for the attributes may correspond tocomputing resource 250 in cloud computing environment 230. In otherimplementations, the computing servers selected by the attribute sharingplatform to compute values for the attributes may be outside of cloudcomputing environment 230. In other implementations, the computingservers selected by the attribute sharing platform to compute values forthe attributes may be separate from cloud computing environment 230 andmay communicate with attribute sharing platform 240 via network 260.

Computing resource 250 includes one or more personal computers,workstation computers, server devices, or another type of computationand/or communication device. In some implementations, computing resource250 may host attribute sharing platform 240. The cloud resources mayinclude compute instances executing in computing resource 250, storagedevices provided in computing resource 250, data transfer devicesprovided by computing resource 250, etc. In some implementations,computing resource 250 may communicate with other computing resource 250via wired connections, wireless connections, or a combination of wiredand wireless connections.

As further shown in FIG. 2, computing resource 250 may include a groupof cloud resources, such as one or more applications (APPs) 250-1, oneor more virtual machines (VMs) 250-2, virtualized storage (VSs) 250-3,one or more hypervisors (HYPs) 250-4, or the like.

Application 250-1 includes one or more software applications that may beprovided to or accessed by client device 210. Application 250-1 mayeliminate a need to install and execute the software applications onclient device 210. For example, application 250-1 may include softwareassociated with attribute sharing platform 240 and/or any other softwarecapable of being provided via cloud computing environment 230. In someimplementations, one application 250-1 may send/receive informationto/from one or more other applications 250-1, via virtual machine 250-2.

Virtual machine 250-2 includes a software implementation of a machine(e.g., a computer) that executes programs like a physical machine.Virtual machine 250-2 may be either a system virtual machine or aprocess virtual machine, depending upon use and degree of correspondenceto any real machine by virtual machine 250-2. A system virtual machinemay provide a complete system platform that supports execution of acomplete operating system (OS). A process virtual machine may execute asingle program and may support a single process. In someimplementations, virtual machine 250-2 may execute on behalf of a user(e.g., client device 210), and may manage infrastructure of cloudcomputing environment 230, such as data management, synchronization, orlong-duration data transfers.

Virtualized storage 250-3 includes one or more storage systems and/orone or more devices that use virtualization techniques within thestorage systems or devices of computing resource 250. In someimplementations, within the context of a storage system, types ofvirtualizations may include block virtualization and filevirtualization. Block virtualization may refer to abstraction (orseparation) of logical storage from physical storage so that the storagesystem may be accessed without regard to physical storage orheterogeneous structure. The separation may permit administrators of thestorage system flexibility in how the administrators manage storage forend users. File virtualization may eliminate dependencies between dataaccessed at a file level and a location where files are physicallystored. This may enable optimization of storage use, serverconsolidation, and/or performance of non-disruptive file migrations.

Hypervisor 250-4 provides hardware virtualization techniques that allowmultiple operating systems (e.g., “guest operating systems”) to executeconcurrently on a host computer, such as computing resource 250.Hypervisor 250-4 may present a virtual operating platform to the guestoperating systems and may manage the execution of the guest operatingsystems. Multiple instances of a variety of operating systems may sharevirtualized hardware resources.

Network 260 includes one or more wired and/or wireless networks. Forexample, network 260 may include a communications network, atelecommunications network, a cellular network (e.g., a long-termevolution (LTE) network, a code division multiple access (CDMA) network,a 3G network, a 4G network, a 5G network, another type of nextgeneration network, etc.), a public land mobile network (PLMN), a localarea network (LAN), a wide area network (WAN), a metropolitan areanetwork (MAN), a telephone network (e.g., the Public Switched TelephoneNetwork (PSTN)), a private network, an ad hoc network, an intranet, theInternet, a fiber optic-based network, a cloud computing network, or thelike, and/or a combination of these or other types of networks.

The number and arrangement of devices and networks shown in FIG. 2 areprovided as an example. In practice, there may be additional devicesand/or networks, fewer devices and/or networks, different devices and/ornetworks, or differently arranged devices and/or networks than thoseshown in FIG. 2. Furthermore, two or more devices shown in FIG. 2 may beimplemented within a single device, or a single device shown in FIG. 2may be implemented as multiple, distributed devices. Additionally, oralternatively, a set of devices (e.g., one or more devices) ofenvironment 200 may perform one or more functions described as beingperformed by another set of devices of environment 200.

FIG. 3 is a diagram of example components of a device 300. Device 300may correspond to client device 210, application server 220, attributesharing platform 240, and/or computing resource 250. In someimplementations, client device 210, application server 220, attributesharing platform 240, and/or computing resource 250 may include one ormore devices 300 and/or one or more components of device 300. As shownin FIG. 3, device 300 may include a bus 310, a processor 320, a memory330, a storage component 340, an input component 350, an outputcomponent 360, and a communication interface 370.

Bus 310 includes a component that permits communication among thecomponents of device 300. Processor 320 is implemented in hardware,firmware, or a combination of hardware and software. Processor 320 is acentral processing unit (CPU), a graphics processing unit (GPU), anaccelerated processing unit (APU), a microprocessor, a microcontroller,a digital signal processor (DSP), a field-programmable gate array(FPGA), an application-specific integrated circuit (ASIC), or anothertype of processing component. In some implementations, processor 320includes one or more processors capable of being programmed to perform afunction. Memory 330 includes a random access memory (RAM), a read onlymemory (ROM), and/or another type of dynamic or static storage device(e.g., a flash memory, a magnetic memory, and/or an optical memory) thatstores information and/or instructions for use by processor 320.

Storage component 340 may store information and/or software related tothe operation and use of device 300. For example, storage component 340may include a hard disk (e.g., a magnetic disk, an optical disk, amagneto-optic disk, and/or a solid state disk), a compact disc (CD), adigital versatile disc (DVD), a floppy disk, a cartridge, a magnetictape, and/or another type of non-transitory computer-readable medium,along with a corresponding drive.

Input component 350 may include a component that permits device 300 toreceive information, such as via user input (e.g., a touch screendisplay, a keyboard, a keypad, a mouse, a button, a switch, and/or amicrophone). Additionally, or alternatively, input component 350 mayinclude a sensor for sensing information (e.g., a global positioningsystem (GPS) component, an accelerometer, a gyroscope, and/or anactuator). Output component 360 includes a component that providesoutput information from device 300 (e.g., a display, a speaker, and/orone or more light-emitting diodes (LEDs)).

Communication interface 370 may include a transceiver-like component(e.g., a transceiver and/or a separate receiver and transmitter) thatenables device 300 to communicate with other devices, such as via awired connection, a wireless connection, or a combination of wired andwireless connections. Communication interface 370 may permit device 300to receive information from another device and/or provide information toanother device. For example, communication interface 370 may include anEthernet interface, an optical interface, a coaxial interface, aninfrared interface, a radio frequency (RF) interface, a universal serialbus (USB) interface, a Wi-Fi interface, a cellular network interface, orthe like.

Device 300 may perform one or more of the processes described herein.Device 300 may perform these processes based on processor 320 executingsoftware instructions stored by a non-transitory computer-readablemedium, such as memory 330 and/or storage component 340. Acomputer-readable medium is defined herein as a non-transitory memorydevice. A memory device includes memory space within a single physicalstorage device or memory space spread across multiple physical storagedevices.

Software instructions may be read into memory 330 and/or storagecomponent 340 from another computer-readable medium or from anotherdevice via communication interface 370. When executed, softwareinstructions stored in memory 330 and/or storage component 340 may causeprocessor 320 to perform one or more processes described herein.Additionally, or alternatively, hardwired circuitry may be used in placeof or in combination with software instructions to perform one or moreprocesses described herein. Thus, implementations described herein arenot limited to any specific combination of hardware circuitry andsoftware.

The number and arrangement of components shown in FIG. 3 are provided asan example. In practice, device 300 may include additional components,fewer components, different components, or differently arrangedcomponents than those shown in FIG. 3. Additionally, or alternatively, aset of components (e.g., one or more components) of device 300 mayperform one or more functions described as being performed by anotherset of components of device 300.

FIG. 4 is a flow chart of an example process 400 for sharing attributecomputation using an attribute sharing platform. In someimplementations, one or more process blocks of FIG. 4 may be performedby an attribute sharing platform (e.g., attribute sharing platform 240).In some implementations, one or more process blocks of FIG. 4 may beperformed by another device or a group of devices separate from orincluding attribute sharing platform 240, such as client device 210, orapplication server 220.

As shown in FIG. 4, process 400 may include receiving information for anattribute to be included in a shared attribute library, wherein theinformation includes an attribute identifier, one or more data variablesneeded to compute a value of the attribute, and a source code forcomputing the value of the attribute, and wherein the source code iswritten in a first programming language (block 410). For example, theattribute sharing platform (e.g., attribute sharing platform 240, usingcomputing resource 250, processor 320, memory 330, storage component340, input component 350, communication interface 370, and/or the like)may receive the information for the attribute to be included in theshared attribute library, as described with regard to FIGS. 1A-1D. Insome implementations, the information received by the attribute sharingplatform includes an attribute identifier, one or more data variablesneeded to compute the value of the attribute, and a source code forcomputing the value of the attribute. In some implementations, thesource code is written in a first programming language.

As further shown in FIG. 4, process 400 may include receiving a firstrequest to compute the value of the attribute based on a first set ofdata variables from a first type of data processing application (block420). For example, the attribute sharing platform (e.g., attributesharing platform 240, using computing resource 250, processor 320,memory 330, storage component 340, input component 350, communicationinterface 370, and/or the like) may receive the first request to computethe value of the attribute based on the first set of data variables fromthe first type of data processing application, as described with regardto FIGS. 1A-1D.

As further shown in FIG. 4, process 400 may include receiving a secondrequest to compute the value of the attribute based on a second set ofdata variables from a second type of data processing application that isdifferent than the first type of data processing application (block430). For example, the attribute sharing platform (e.g., attributesharing platform 240, using computing resource 250, processor 320,memory 330, storage component 340, input component 350, communicationinterface 370, and/or the like) may receive the second request tocompute the value of the attribute based on the second set of datavariables from the second type of data processing application that isdifferent than the first type of data processing application, asdescribed with regard to FIGS. 1A-1D.

As further shown in FIG. 4, process 400 may include selecting, by theprocessor, a computing server from a plurality of computing servers,wherein the computing server is configured to execute the firstprogramming language to compute the value of the attribute based on thefirst set of data variables and the second set of data variables, andwherein at least two of the plurality of computing servers areassociated with different programming languages (block 440). Forexample, the attribute sharing platform (e.g., attribute sharingplatform 240, using computing resource 250, processor 320, memory 330,storage component 340, and/or the like) may select a computing serverfrom a plurality of computing servers, as described with regard to FIGS.1A-1D. In some implementations, the computing server is configured toexecute the first programming language to compute the value of theattribute based on the first set of data variables and the second set ofdata variables. In some implementations, at least two of the pluralityof computing servers are associated with different programminglanguages.

As further shown in FIG. 4, process 400 may include receiving a firstattribute value based on using the source code to compute the value ofthe attribute based on the first set of data variables (block 450). Forexample, the attribute sharing platform (e.g., attribute sharingplatform 240, using computing resource 250, processor 320, memory 330,storage component 340, input component 350, communication interface 370,and/or the like) may receive the first attribute value based on usingthe source code to compute the value of the attribute based on the firstset of data variables, as described with regard to FIGS. 1A-1D.

As further shown in FIG. 4, process 400 may include receiving a secondattribute value based on using the source code to compute the value ofthe attribute based on the second set of data variables (block 460). Forexample, the attribute sharing platform (e.g., attribute sharingplatform 240, using computing resource 250, processor 320, memory 330,storage component 340, input component 350, communication interface 370,and/or the like) may receive the second attribute value based on usingthe source code to compute the value of the attribute based on thesecond set of data variables, as described with regard to FIGS. 1A-1D.

As further shown in FIG. 4, process 400 may include transmitting thefirst attribute value as an input for the first type of data processingapplication (block 470). For example, the attribute sharing platform(e.g., attribute sharing platform 240, using computing resource 250,processor 320, memory 330, storage component 340, output component 360,communication interface 370, and/or the like) may transmit the firstattribute value as the input for the first type of data processingapplication, as described with regard to FIGS. 1A-1D.

As further shown in FIG. 4, process 400 may include transmitting thesecond attribute value as an input for the second type of dataprocessing application (block 480). For example, the attribute sharingplatform (e.g., attribute sharing platform 240, using computing resource250, processor 320, memory 330, storage component 340, output component360, communication interface 370, and/or the like) may transmit thesecond attribute value as the input for the second type of dataprocessing application, as described with regard to FIGS. 1A-1D.

Process 400 may include additional aspects, such as any singleimplementation or any combination of aspects described below and/or inconnection with the one or more processes described elsewhere herein

In some implementations, the first type of data processing applicationand the second type of data processing application are at least one of abatch application, a streaming application, or an API-based application.In some implementations, the first set of data variables and the secondset of data variables include a same quantity of data points and a sametype of data attributes.

In some implementations, the first type of data processing applicationor the second type of data processing application is implementing asecond programming language that is different than the first programminglanguage. In some implementations, at least one of the first type ofdata processing application or the second type of data processingapplication is an application that operates based on a trigger. In someimplementations, at least one of the first type of data processingapplication or the second type of data processing application is anapplication that does not operate based on a trigger.

In some implementations, process 400 may include validating the firstrequest by verifying that the first set of data variables includes theone or more data variables needed to compute the value of the attributeand validating the second request by verifying that the second set ofdata variables includes the one or more data variables needed to computethe value of the attribute.

In some implementations, selecting the computing server from theplurality of computing servers comprises mapping the attribute to thecomputing server based on the computing server being configured toexecute the first programming language and selecting the computingserver based on the mapping.

Although FIG. 4 shows example blocks of process 400, in someimplementations, process 400 may include additional blocks, fewerblocks, different blocks, or differently arranged blocks than thosedepicted in FIG. 4. Additionally, or alternatively, two or more of theblocks of process 400 may be performed in parallel.

FIG. 5 is a flow chart of a further example process for sharingattribute computation using an attribute sharing platform. In someimplementations, one or more process blocks of FIG. 5 may be performedby an attribute sharing platform 240. In some implementations, one ormore process blocks of FIG. 5 may be performed by another device or agroup of devices separate from or including an attribute sharingplatform 240, such as client device 210, or application server 220.

As shown in FIG. 5, process 500 may include receiving information for anattribute to be included in the shared attribute library, wherein theinformation includes an attribute identifier, one or more data variablesneeded to compute a value of the attribute, and a source code forcomputing the value of the attribute, and wherein the source code iswritten in a first programming language (block 505). For example, theattribute sharing platform (e.g., attribute sharing platform 240, usingcomputing resource 250, processor 320, memory 330, storage component340, input component 350, communication interface 370 and/or the like)may receive information for an attribute to be included in a sharedattribute library, as described with regard to FIGS. 1A-1D. In someimplementations, the information includes an attribute identifier, oneor more data variables needed to compute a value of the attribute, and asource code for computing the value of the attribute. In someimplementations, the source code is written in a first programminglanguage.

As further shown in FIG. 5, process 500 may include receiving a firstrequest to compute the value of the attribute based on a first set ofdata variables from a first type of data processing application (block510). For example, the attribute sharing platform (e.g., attributesharing platform 240, using computing resource 250, processor 320,memory 330, storage component 340, input component 350, communicationinterface 370, and/or the like) may receive a first request to computethe value of the attribute based on a first set of data variables fromthe first type of data processing application, as described with regardto FIGS. 1A-1D.

As further shown in FIG. 5, process 500 may include validating the firstrequest by verifying that the first set of data variables includes theone or more data variables needed to compute the value of the attribute(block 515). For example, the attribute sharing platform (e.g.,attribute sharing platform 240, using computing resource 250, processor320, memory 330, storage component 340, input component 350,communication interface 370, and/or the like) may validate the firstrequest by verifying that the first set of data variables includes theone or more data variables needed to compute the value of the attribute,as described with regard to FIGS. 1A-1D.

As further shown in FIG. 5, process 500 may include receiving a secondrequest to compute the value of the attribute based on a second set ofdata variables from a second type of data processing application that isdifferent than the first type of data processing application (block520). For example, the attribute sharing platform (e.g., attributesharing platform 240, using computing resource 250, processor 320,memory 330, storage component 340, input component 350, communicationinterface 370, and/or the like) may receive a second request to computethe value of the attribute based on a second set of data variables fromthe second type of data processing application that is different thanthe first type of data processing application, as described with regardto FIGS. 1A-1D.

As further shown in FIG. 5, process 500 may include validating thesecond request by verifying that the second set of data variablesincludes the one or more data variables needed to compute the value ofthe attribute (block 525). For example, the attribute sharing platform(e.g., attribute sharing platform 240, using computing resource 250,processor 320, memory 330, storage component 340, input component 350,communication interface 370, and/or the like) may validate the secondrequest by verifying that the second set of data variables includes theone or more data variables needed to compute the value of the attribute,as described with regard to FIGS. 1A-1D.

As further shown in FIG. 5, process 500 may include selecting acomputing server from a plurality of computing servers, wherein thecomputing server is configured to execute the first programming languageto compute the value of the attribute based on the first set of datavariables and the second set of data variables, and wherein at least twoof the plurality of computing servers are associated with differentprogramming languages (block 530). For example, the attribute sharingplatform (e.g., attribute sharing platform 240, using computing resource250, processor 320, memory 330, storage component 340, input component350, communication interface 370, and/or the like) may select acomputing server from the plurality of computing servers, as describedwith regard to FIGS. 1A-1D. In some implementations, the computingserver is configured to execute the first programming language tocompute the value of the attribute based on the first set of datavariables and the second set of data variables. In some implementations,at least two of the plurality of computing servers are associated withdifferent programming languages.

As further shown in FIG. 5, process 500 may include receiving a firstattribute value based on using the source code to compute the value ofthe attribute based on the first set of data variables (block 535). Forexample, the attribute sharing platform (e.g., attribute sharingplatform 240, using computing resource 250, processor 320, memory 330,storage component 340, input component 350, communication interface 370,and/or the like) may receive the first attribute value based on usingthe source code to compute the value of the attribute based on the firstset of data variables, as described with regard to FIGS. 1A-1D.

As further shown in FIG. 5, process 500 may include receiving a secondattribute value based on using the source code to compute the value ofthe attribute based on the second set of data variables (block 540). Forexample, the attribute sharing platform (e.g., attribute sharingplatform 240, using computing resource 250, processor 320, memory 330,storage component 340, input component 350, communication interface 370,and/or the like) may receive the second attribute value based on usingthe source code to compute the value of the attribute based on thesecond set of data variables, as described with regard to FIGS. 1A-1D.

As further shown in FIG. 5, process 500 may include transmitting thefirst attribute value as an input for the first type of data processingapplication (block 545). For example, the attribute sharing platform(e.g., attribute sharing platform 240, using computing resource 250,processor 320, memory 330, storage component 340, input component 350,communication interface 370, and/or the like) may transmit the firstattribute value as an input for the first type of data processingapplication, as described with regard to FIGS. 1A-1D.

As further shown in FIG. 5, process 500 may include transmitting thesecond attribute value as an input for the second type of dataprocessing application (block 550). For example, the attribute sharingplatform (e.g., attribute sharing platform 240, using computing resource250, processor 320, memory 330, storage component 340, input component350, communication interface 370, and/or the like) may transmit thesecond attribute value as an input for the second type of dataprocessing application, as described with regard to FIGS. 1A-1D.

Process 500 may include additional aspects, such as any singleimplementation or any combination of aspects described below and/or inconnection with the one or more processes described elsewhere herein.

In some implementations, the first type of data processing applicationand the second type of data processing application are at least one of abatch application, a streaming application, or an API-based application.In some implementations, the first set of data variables and the secondset of data variables include a same quantity of data points and a sametype of data attributes. In some implementations, the first type of dataprocessing application or the second type of data processing applicationis implementing a second programming language that is different than thefirst programming language.

In some implementations, at least one of the first type of dataprocessing application or the second type of data processing applicationis an application that operates based on a trigger. In someimplementations, the trigger is a time-based trigger. In someimplementations, the trigger is a request from an API-endpoint.

In some implementations, process 500 may include mapping the attributeto the computing server based on the computing server being configuredto execute the first programming language and selecting the computingserver based on the map of the attribute to the computer server.

Although FIG. 5 shows example blocks of process 500, in someimplementations, process 500 may include additional blocks, fewerblocks, different blocks, or differently arranged blocks than thosedepicted in FIG. 5. Additionally, or alternatively, two or more of theblocks of process 500 may be performed in parallel.

FIG. 6 is a flow chart of a further example process for sharingattribute computation using an attribute sharing platform. In someimplementations, one or more process blocks of FIG. 6 may be performedby an attribute sharing platform 240. In some implementations, one ormore process blocks of FIG. 6 may be performed by another device or agroup of devices separate from or including an attribute sharingplatform 240, such as client device 210, or application server 220.

As shown in FIG. 6, process 600 may include receiving information for anattribute to be included in a shared attribute library, wherein theinformation includes an attribute identifier, one or more data variablesneeded to compute a value of the attribute, and a source code forcomputing the value of the attribute, and wherein the source code iswritten in a first programming language (block 610). For example, theattribute sharing platform (e.g., attribute sharing platform 240, usingcomputing resource 250, processor 320, memory 330, storage component340, input component 350, communication interface 370, and/or the like)may receive information for an attribute to be included in a sharedattribute library, as described with regard to FIGS. 1A-1D. In someimplementations, the information includes an attribute identifier, oneor more data variables needed to compute a value of the attribute, and asource code for computing the value of the attribute. In someimplementations, wherein the source code is written in a firstprogramming language.

As further shown in FIG. 6, process 600 may include receiving a firstrequest to compute the value of the attribute based on a first set ofdata variables from a first type of data processing application (block620). For example, the attribute sharing platform (e.g., attributesharing platform 240, using computing resource 250, processor 320,memory 330, storage component 340, input component 350, communicationinterface 370, and/or the like) may receive the first request to computethe value of the attribute based on the first set of data variables fromthe first type of data processing application, as described with regardto FIGS. 1A-1D.

As further shown in FIG. 6, process 600 may include receiving a secondrequest to compute the value of the attribute based on a second set ofdata variables from a second type of data processing application,wherein the second type of data processing application is different thanthe first type of data processing application, and wherein the firsttype of data processing application or the second type of dataprocessing application is implementing a second programming languagethat is different than the first programming language (block 630). Forexample, the attribute sharing platform (e.g., attribute sharingplatform 240, using computing resource 250, processor 320, memory 330,storage component 340, input component 350, communication interface 370,and/or the like) may receive a second request to compute the value ofthe attribute based on a second set of data variables from the secondtype of data processing application, as described with regard to FIGS.1A-1D. In some implementations, the second type of data processingapplication is different than the first type of data processingapplication. In some implementations, the first type of data processingapplication or the second type of data processing application isimplementing a second programming language that is different than thefirst programming language.

As further shown in FIG. 6, process 600 may include selecting acomputing server from a plurality of computing servers, wherein thecomputing server is configured to execute the first programming languageto compute the value of the attribute based on the first set of datavariables and the second set of data variables, and wherein at least twoof the plurality of computing servers are associated with differentprogramming languages (block 640). For example, the attribute sharingplatform (e.g., attribute sharing platform 240, using computing resource250, processor 320, memory 330, storage component 340, input component350, communication interface 370, and/or the like) may select acomputing server from the plurality of computing servers, as describedwith regard to FIGS. 1A-1D. In some implementations, the computingserver is configured to execute the first programming language tocompute the value of the attribute based on the first set of datavariables and the second set of data variables. In some implementations,at least two of the plurality of computing servers are associated withdifferent programming languages.

As further shown in FIG. 6, process 600 may include receiving a firstattribute value based on using the source code to compute the value ofthe attribute based on the first set of data variables (block 650). Forexample, the attribute sharing platform (e.g., attribute sharingplatform 240, using computing resource 250, processor 320, memory 330,storage component 340, input component 350, communication interface 370,and/or the like) may receive the first attribute value based on usingthe source code to compute the value of the attribute based on the firstset of data variables, as described with regard to FIGS. 1A-1D.

As further shown in FIG. 6, process 600 may include receiving a secondattribute value based on using the source code to compute the value ofthe attribute based on the second set of data variables (block 660). Forexample, the attribute sharing platform (e.g., attribute sharingplatform 240, using computing resource 250, processor 320, memory 330,storage component 340, input component 350, communication interface 370,and/or the like) may receive a second attribute value based on using thesource code to compute the value of the attribute based on the secondset of data variables, as described with regard to FIGS. 1A-1D.

As further shown in FIG. 6, process 600 may include transmitting thefirst attribute value as an input for the first type of data processingapplication (block 670). For example, the attribute sharing platform(e.g., attribute sharing platform 240, using computing resource 250,processor 320, memory 330, storage component 340, input component 350,communication interface 370, and/or the like) may transmit the firstattribute value as the input for the first type of data processingapplication, as described with regard to FIGS. 1A-1D.

As further shown in FIG. 6, process 600 may include transmitting thesecond attribute value as an input for the second type of dataprocessing application (block 680). For example, the attribute sharingplatform (e.g., attribute sharing platform 240, using computingresources 250, processor 320, memory 330, storage component 340, inputcomponent 350, communication interface 370, and/or the like) maytransmit the second attribute value as the input for the second type ofdata processing application, as described with regard to FIGS. 1A-1D.

Process 600 may include additional aspects, such as any singleimplementation or any combination of aspects described below and/or inconnection with the one or more processes described elsewhere herein.

In some implementations, process 600 may include validating the firstrequest by verifying that the first set of data variables includes theone or more data variables needed to compute the value of the attributeand validating the second request by verifying that the second set ofdata variables includes the one or more data variables needed to computethe value of the attribute.

In some implementations, process 600 may include mapping the attributeto the computing server based on the computing server being configuredto execute the first programming language and selecting the computingserver based on the mapping.

In some implementations, process 600 may include receiving a thirdrequest to compute the value of the attribute based on a third set ofdata variables from a third type of data processing application. In someimplementations, the third type of data processing application isdifferent than the first type of data processing application and thesecond type of data processing application.

In some implementations, process 600 may include selecting the computingserver from a plurality of computing servers. In some implementations,the computing server is configured to execute the first programminglanguage to compute the value of the attribute based on the third set ofdata variables. In some implementations, process 600 may includereceiving a third attribute value based on using the source code tocompute the value of the attribute based on the third set of datavariables and transmitting the third attribute value as an input for thethird type of data processing application.

Although FIG. 6 shows example blocks of process 600, in someimplementations, process 600 may include additional blocks, fewerblocks, different blocks, or differently arranged blocks than thosedepicted in FIG. 6. Additionally, or alternatively, two or more of theblocks of process 600 may be performed in parallel.

As described herein, providing the attribute sharing platform includingthe shared attribute library standardizes the core computation ofattributes based on using the same source code to compute the sharedattributes for different data processing applications. As a result,calculating the attributes across multiple data processing applicationswithin a data processing system may be consistent, easing the burden ofchange management and simplifying attribute code development andsharing.

Further, the different types of applications implementing differentcomputing languages may access the shared attributes and compute valuesfor the shared attributes according to the same logic or source code asdefined by the attribute sharing platform. Furthermore, standardizingthe messaging that the different types of applications used to requestand receive the attributes, for example, utilizing RPCs, provides astandardized manner in which to request and receive the attributes to beused as input for the different types of data processing applications.

The foregoing disclosure provides illustration and description but isnot intended to be exhaustive or to limit the implementations to theprecise form disclosed. Modifications and variations are possible inlight of the above disclosure or may be acquired from practice of theimplementations.

As used herein, the term component is intended to be broadly construedas hardware, firmware, or a combination of hardware and software.

Certain user interfaces have been described herein and/or shown in thefigures. A user interface may include a graphical user interface, anon-graphical user interface, a text-based user interface, or the like.A user interface may provide information for display. In someimplementations, a user may interact with the information, such as byproviding input via an input component of a device that provides theuser interface for display. In some implementations, a user interfacemay be configurable by a device and/or a user (e.g., a user may changethe size of the user interface, information provided via the userinterface, a position of information provided via the user interface,etc.). Additionally, or alternatively, a user interface may bepre-configured to a standard configuration, a specific configurationbased on a type of device on which the user interface is displayed,and/or a set of configurations based on capabilities and/orspecifications associated with a device on which the user interface isdisplayed.

It will be apparent that systems and/or methods, described herein, maybe implemented in different forms of hardware, firmware, or acombination of hardware and software. The actual specialized controlhardware or software code used to implement these systems and/or methodsis not limiting of the implementations. Thus, the operation and behaviorof the systems and/or methods were described herein without reference tospecific software code—it being understood that software and hardwarecan be designed to implement the systems and/or methods based on thedescription herein.

Even though particular combinations of features are recited in theclaims and/or disclosed in the specification, these combinations are notintended to limit the disclosure of possible implementations. In fact,many of these features may be combined in ways not specifically recitedin the claims and/or disclosed in the specification. Although eachdependent claim listed below may directly depend on only one claim, thedisclosure of possible implementations includes each dependent claim incombination with every other claim in the claim set.

No element, act, or instruction used herein should be construed ascritical or essential unless explicitly described as such. Also, as usedherein, the articles “a” and “an” are intended to include one or moreitems, and may be used interchangeably with “one or more.” Furthermore,as used herein, the term “set” is intended to include one or more items(e.g., related items, unrelated items, a combination of related andunrelated items, etc.), and may be used interchangeably with “one ormore.” Where only one item is intended, the term “one” or similarlanguage is used. Also, as used herein, the terms “has,” “have,”“having,” or the like are intended to be open-ended terms. Further, thephrase “based on” is intended to mean “based, at least in part, on”unless explicitly stated otherwise.

What is claimed is:
 1. A method, comprising: receiving, by a processor,a first request to compute a value of an attribute based on a first setof data variables from a first data processing application; identifying,by the processor and for the attribute, a computing server associatedwith source code for computing the value of the attribute, the sourcecode being written in a first programming language; transmitting, by theprocessor and based on the attribute being mapped to the computingserver, a second request to the computing server, the second requestincluding data specifying: the attribute, and the first set of datavariables, and the computing server being configured to execute thesource code, written in the first programming language, to compute thevalue of the attribute based on the first set of data variables;receiving, by the processor and from the computing server, a firstattribute value based on the source code being used to compute the valueof the attribute; and transmitting, by the processor, the firstattribute value as an input for the first data processing application.2. The method of claim 1, wherein the first data processing applicationis at least one of: a batch application, a streaming application, or anapplication programming interface (API) based application.
 3. The methodof claim 1, wherein identifying the source code comprises: identifyingthe source code from a set of source code, the set of source codeincluding another source code written in a second programming languagethat is different from the first programming language.
 4. The method ofclaim 1, further comprising: identifying the computing server, from aplurality of computing servers, based on a map of attributes to theplurality of computing servers.
 5. The method of claim 4, wherein theplurality of computing servers includes a second computing serverassociated with a second programming language associated with secondsource code for computing a second attribute.
 6. The method of claim 1,wherein identifying the computing server comprises: identifying thecomputing server based on a programming language identifier thatidentifies the first programming language as being associated with thecomputing server.
 7. The method of claim 1, further comprising:validating the first request by verifying that the first set of datavariables includes the first set of data variables needed to compute thevalue of the attribute.
 8. The method of claim 1, further comprising:mapping the attribute to the computing server based on the computingserver being configured to execute the first programming language, andselecting the computing server, from a plurality of computing servers,based on the mapping.
 9. A device, comprising: a memory deviceconfigured to store a shared attribute library; and one or moreprocessors configured to: receive a first request to compute a value ofan attribute based on a first set of data variables from a first dataprocessing application; identify, for the attribute, a computing serverassociated with source code for computing the value of the attribute,the source code being written in a first programming language; transmit,based on the attribute being mapped to the computing server, a secondrequest to the computing server, the second request including dataspecifying the attribute and the first set of data variables, and thecomputing server being configured to execute the source code, written inthe first programming language, to compute the value of the attributebased on the first set of data variables; receive, from the computingserver, a first attribute value based on the source code being used tocompute the value of the attribute; and transmit the first attributevalue as an input for the first data processing application.
 10. Thedevice of claim 9, wherein the first data processing application is atleast one of: a batch application, a streaming application, or anapplication programming interface (API) based application.
 11. Thedevice of claim 9, wherein the one or more processors, when identifyingthe source code, are further configured to: identify the source codefrom a set of source code, the set of source code including anothersource code written in a second programming language.
 12. The device ofclaim 9, wherein the one or more processors are further configured to:identify the computing server, from a plurality of computing servers,based on a map of attributes to the plurality of computing servers. 13.The device of claim 9, wherein the first data processing application isan application that operates based on a trigger.
 14. The device of claim13, wherein the trigger is a time-based trigger.
 15. The device of claim13, wherein the trigger is a request from an application programminginterface (API) endpoint.
 16. The device of claim 9, wherein the one ormore processors are further configured to: map the attribute to thecomputing server based on the computing server being configured toexecute the first programming language, and select the computing serverbased on the map of the attribute to the computer server.
 17. Anon-transitory computer-readable medium storing instructions, theinstructions comprising: one or more instructions that, when executed byone or more processors, cause the one or more processors to: receive afirst request to compute a value of an attribute based on a first set ofdata variables from a first data processing application; identify, forthe attribute, a computing server associated with source code forcomputing the value of the attribute, the source code being written in afirst programming language; transmit, based on the attribute beingmapped to the computing server, a second request to the computingserver, the second request including data specifying the attribute andthe first set of data variables, and the computing server beingconfigured to execute the source code, written in the first programminglanguage, to compute the value of the attribute based on the first setof data variables; receive, from the computing server, a first attributevalue based on the source code being used to compute the value of theattribute; and transmit the first attribute value as an input for thefirst data processing application.
 18. The non-transitorycomputer-readable medium of claim 17, wherein the one or moreinstructions, when executed by the one or more processors, further causethe one or more processors to: validate the first request by verifyingthat the first set of data variables includes the first set of datavariables needed to compute the value of the attribute.
 19. Thenon-transitory computer-readable medium of claim 17, wherein the one ormore instructions, when executed by the one or more processors, furthercause the one or more processors to: map the attribute to the computingserver based on the computing server being configured to execute thefirst programming language; and selecting the computing server based onthe mapping.
 20. The non-transitory computer-readable medium of claim17, wherein the one or more instructions, when executed by the one ormore processors, further cause the one or more processors to: receive athird request to compute the value of the attribute based on a secondset of data variables from a second data processing application, whereinthe second data processing application is different than the first dataprocessing application; select the computing server from a plurality ofcomputing servers, wherein the computing server is configured to executethe source code, written in the first programming language, to computethe value of the attribute based on the second set of data variables;receive a second attribute value based on using the source code tocompute the value of the attribute based on the second set of datavariables; and transmit the second attribute value as an input for thesecond data processing application.